Journal of Majlesi Journal of Mechatronic Systems
Volume:4 Issue: 2, Jun 2015

In this paper present a new surface in an active sliding mode to synchronize two chaotic systems. To verify the capability of the proposed scheme, signals are also contaminated by measurement noise. The integral acting surface produces a dynamics for error, where the appropriate eigenvalues are easily assigned. Using this surface, calculation of parameters of the controller becomes simpler than the classical alternative. A sufficient condition, as a guideline of the designated procedure, is dedicated to provide a robust stability of the error dynamics. Finally, a simulation study is performed to verify the robustness and effectiveness of the proposed control strategy.

Access to a model of this type of turbine that can represent the characteristics of the gas turbine will help us in analysis and design of suitable controllers. In this paper, after identification and determination of the parameters of the turbine, we will evaluate the suggested model. To identify the tested system and based on the input and output samples obtained from the results of practical experiments conducted on a real system and extracted from the turbine values a model of system is built and then using identification algorithm the overall system model is obtained. Then we use MATLAB to identify the turbine model. Conducted validation indicating the proximity of the identified model and the actual model.

Funding for training human resources in most countries is very important and costly. Hence in training, prediction of students with expelled risky is one of the today's key issues and researches. There are imbalances in the training data that causes reduce prediction accuracy in fail students. In this paper, experiments based on data mining techniques have been tried to improve prediction accuracy of fail students. To do this, data from the UCI site are used that contains 5820 records in Turkish students. First, the training data are clustered to select the most appropriate algorithm, Farthest First, and then by doing experiments, best Features including the fitness level of instructor and student's attendance level and the best Test option, 90% for training data, are selected. Questionnaire is used to Weight features. Finally, the cost-sensitive classification algorithms have been implemented with the proposed cost matrix and the model provided the best results. Results prove that this model can play an important role in promoting science education centers with an accuracy rate of 96.47%, TP rate 99.2% and precision rate of 96%.

In this paper, the design of a controller for a nonlinear electro- pneumatic system of six degrees of freedom Stewart is discussed. Since the Stewart’s mechanism is a nonlinear system, nonlinear control methods should be used to control it and, in this paper, the sliding mode control (SMC) is used. In this method, at first a sliding surface is defined so that the dynamics of the system are restricted to it. In the next step, feedback control law is defined so that the paths outside the sliding surface to reach sliding surface in a limited time and stay on them. Thus, the closed loop system of SMC is robust against uncertainties and external disturbances. Finally, through computer simulation in the matlab software, the desired performance of the designed controller is shown.

Recently due to limited resources and high cost of energy, optimization of energy consumption in many aspects is under study by researchers. The main purpose of this study is to optimize a robot with four degrees of freedom to find the minimum energy consumption. At first, the kinematic, inverse kinematic and dynamic analysis of the robot is performed and then the energy equations of actuators are predicted. The default path of the robot is assumed as a five order polynomial and the consumption energy of the actuators for the motion of end-effector is obtained. For optimizing the path and comparing it to the default path, two random points in the workspace of the robot are selected and then five order spline in the robot workspace is defined. In addition, the continuity conditions are satisfied and the energy consumption for the new path is predicted. Finally, the genetic algorithm toolbox of MATLAB is applied for optimization. The energy function of the actuators are defined as the objective function and the workspace of the robot set as the guess range of spline points. Finally, the optimum path with minimum actuator energy consumption is obtained.

In this paper, a method has been presented for the sensor-less control of the Brushless DC (BLDC) motor. The method proposed in this paper, is based on detection of back EMF. The presented method has been able to solve the problems of the methods of sensor-less control in low speed. It also has an almost exact operation. Back EMF Difference has been used in this method, so the need for Neutral Point has been removed. This method is a simple one and it can be applied using a Resistance and a Microprocessor. Hysteresis Current regulation has been used in this method in order to control the motor speed. This method has been simulated in MATLABSIMULINK for evaluation and the results have been analyzed.